One important barrier to the successful dissemination of evidence-based practices (EBP) in mental health is the need to train therapists effectively and affordably. To date, the most common training methods in mental health tend to lead to increases in knowledge about EBP but not to skill development or behavior change. The present study will integrate state-of-the art technologies, prior literature on therapist training, and learning theory to develop an accessible and engaging practice component for a traditional online EBP training, with the goal of increasing trainees' skill in a specific EBP in a cost-effective manner. Specifically, the proposed study will have two phases: first, it will first develop a high-quality traditional online training to teach clinicians-in-training how to conduct evidence-based suicide risk assessment. In addition, it will develop an interactive computerized practice client with whom trainees can interact in order to rehearse newly learned concepts and build skill. These training components will be developed in consultation with content and technology experts to ensure the best possible quality of trainings. In its second phase, the present study will test the acceptability and efficacy of the virtual client practice tool by randomly assigning approximately 300 clinicians in training to receive the training as usual, the traditional online training alone, or the traditional online training plus the virtual practice component. It is anticipated that trainees interacting with the practice client will report higher training satisfaction, will show higher training use, and will obtain higher scores on questionnaires and simulations measuring skill in risk assessment than trainees receiving the training as usual or the traditional online training only. Trainees' risk assessment knowledge will also be measured, although no group differences are expected in this domain. The proposed study is a randomized-controlled trial, with measures collected at baseline, post-training, and follow-up (60 days). Trainees who agree to participate will be given access to the study measures (satisfaction, knowledge, and skill) online. Training use will be unobtrusively measured through automated recording of training access data. Planned data analyses will use hierarchical linear regression to predict scores on each study outcome from group status, controlling for training program. Any variables failing a randomization check will also be controlled for. Hierarchical linear modeling will allow for analysis of repeated measures while accounting for the nested structure of the proposed dataset (trainees nested within courses). The proposed study addresses one of the four primary objectives of the NIH: to help close the gap between the development of new, research-tested interventions and their wide-spread use by those most in need (Strategic Objective 4). The proposed study is also consistent with the goal of this funding mechanism to improve the quality of the training environment. Finally, by developing a potentially cost-effective therapist training tool that can be easily deployed to remote areas, it has the potential to improve the quality of care to underserved populations and contribute to the NIH goal of eliminating health disparities.